Enhanced DeepLab Based Nerve Segmentation with Optimized Tuning

Akhil John Thomas; Christiaan Boerkamp

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arXiv · 2507.13394

Enhanced DeepLab Based Nerve Segmentation with Optimized Tuning

Akhil John Thomas·Christiaan Boerkamp

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Abstract

Nerve segmentation is crucial in medical imaging for precise identification of nerve structures. This study presents an optimized DeepLabV3-based segmentation pipeline that incorporates automated threshold fine-tuning to improve segmentation accuracy. By refining preprocessing steps and implementing parameter optimization, we achieved a Dice Score of 0.78, an IoU of 0.70, and a Pixel Accuracy of 0.95 on ultrasound nerve imaging. The results demonstrate significant improvements over baseline models and highlight the importance of tailored parameter selection in automated nerve detection.

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Akhil John Thomas, Christiaan Boerkamp. 2025-07-16. Enhanced DeepLab Based Nerve Segmentation with Optimized Tuning. https://arxiv.org/abs/2507.13394

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